{"id":"W2610119122","doi":"","title":"Chaos, order and uncertainty when writing narrative for animation","year":2017,"lang":"en","type":"dissertation","venue":"Minerva Access (University of Melbourne)","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Melbourne; McGill University","keywords":"Narrative; Animation; Order (exchange); Computer science; CHAOS (operating system); Computer graphics (images); Art; Literature; Computer security; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003365652,0.0002193984,0.0003909845,0.000224503,0.0007987885,0.0003322326,0.001912117,0.0002383381,0.00007031505],"category_scores_gemma":[0.0002040976,0.0002616923,0.0001035362,0.000135944,0.0001251363,0.002048871,0.0002125297,0.0001778274,0.000004180409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005885891,"about_ca_system_score_gemma":0.0001809402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001970276,"about_ca_topic_score_gemma":0.007227623,"domain_scores_codex":[0.9987119,0.00005121861,0.0002216653,0.0004954297,0.000277515,0.0002422764],"domain_scores_gemma":[0.9977004,0.000162985,0.0007856349,0.000440602,0.0008296743,0.00008070964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002717377,0.0001390332,0.0007831237,0.001060772,0.0002669266,0.00003261556,0.1617439,0.0003660065,0.002620862,0.02590862,0.007925107,0.7988813],"study_design_scores_gemma":[0.002387867,0.0008629425,0.02784011,0.003839955,0.0005679692,0.0000285393,0.1907348,0.6058273,0.01412422,0.1091035,0.04109084,0.003592069],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6760551,0.0007557111,0.3043668,0.003517676,0.001244597,0.001286964,0.0000512552,0.0001587225,0.01256316],"genre_scores_gemma":[0.8808382,0.0003231689,0.06517565,0.00008548907,0.0003014072,0.00000813397,0.0003845414,0.00004801159,0.05283543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7952893,"threshold_uncertainty_score":0.9999835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05213686852786371,"score_gpt":0.3185787041966902,"score_spread":0.2664418356688265,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}